Evidence map›Paper›PMID 40489918›Full record

ArticleNeuroImage. Clinical2025

Structural connectome manifold changes related to body mass index and their associations with eating psychopathology.

Yurim Jang, Jong Young Namgung, Eunchan Noh, Bo-Yong Park

Abstract read
In one paragraph

Article in NeuroImage. Clinical, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Yurim JangDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea; BK21 Four Institute of Precision Public Health, Seoul, Republic of Korea.
Jong Young NamgungDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea.
Eunchan NohCollege of Medicine, Inha University, Incheon, Republic of Korea.
Bo-Yong ParkDepartment of Brain and Cognitive Engineering, Korea University, Seoul, Republic of Korea; Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea. Electronic address: boyongpark@korea.ac.kr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Brain connectome analysis provides insights into body mass index (BMI)-related brain topology and cognitive functions. While alterations in the brain connectome have been observed in individuals with high BMI, evidence regarding BMI-based structural connectome alteration remains limited. In this study, we analyzed diffusion magnetic resonance imaging tractography-derived structural connectivity from 283 neurologically healthy participants by generating low-dimensional features using dimensionality reduction techniques. Two key metrics were calculated: manifold eccentricity, which indicates the relative distance of each brain region from the center of the low-dimensional manifold space, and manifold differentiation, which represents the distance between brain regions within the manifold space. Our findings revealed that individuals with high BMI exhibited greater expansion and differentiation in the control, default mode, and somatomotor networks, reflecting increased network segregation. In contrast, the visual and limbic networks displayed higher integration. Furthermore, network communication measures based on search information and path transitivity indicated less efficient communication between low-level sensory and higher-order transmodal networks in individuals with high BMI. Finally, significant associations were identified between the manifold features in the prefrontal and somatomotor regions and eating behaviors, as assessed by self-report measures from the Eating Disorder Examination Questionnaire (EDEQ) and the Three-Factor Eating Questionnaire (TFEQ). These results highlight the critical role of structural connectome organization in describing BMI and eating behaviors.

Indexed as

Body Mass IndexBrainConnectomeFeeding and Eating DisordersFeeding BehaviorNerve NetAdultDiffusion Tensor ImagingFemaleHumansMaleYoung AdultBody mass indexConnectome manifoldEating behaviorStructural connectivity

Identifiers

PMID40489918
PMCPMC12174600

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.